After decades of massive digitisation, an unprecedented number of historical documents are
available in digital format, along with their machine-readable texts. While this represents a …

How to study media diversity has become a major concern in today's media landscape.
Many expect that algorithmic filtering and a shift of audiences from legacy media to new …

The experimental landscape in natural language processing for social media is too
fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics …

Driven by 'success stories' reported by private sector firms, government agencies have also
started adopting various Artificial Intelligence (AI) technologies in diverse domains (eg …

We present MultiCoNER, a large multilingual dataset for Named Entity Recognition that
covers 3 domains (Wiki sentences, questions, and search queries) across 11 languages, as …

We present the findings of SemEval-2022 Task 11 on Multilingual Complex Named Entity
Recognition MULTICONER. Divided into 13 tracks, the task focused on methods to identify …

This shared task focuses on identifying unusual, previously-unseen entities in the context of
emerging discussions. Named entities form the basis of many modern approaches to other …

In this paper, we present our multi-channel neural architecture for recognizing emerging
named entity in social media messages, which we applied in the Novel and Emerging …

We present a new dataset comprised of 210,532 tokens evenly drawn from 100 different
English-language literary texts annotated for ACE entity categories (person, location, geo …

Despite recent dramatic successes, natural language processing (NLP) is not ready to
address a variety of real‐world problems. Its reliance on large standard corpora, a training …